Kuijper, ArjanRus, SilviaGutjahr, ChristianChristianGutjahr2022-03-072022-03-072018https://publica.fraunhofer.de/handle/publica/281898We are surrounded by textiles in our everyday live. Making them capable of local monitoring and computing is already a growing field of research in the area of Smart Home and Ambient Assisted Living. Equipping usual furniture with sensors and simple computational elements can provide useful information about the user and help with identifying emergency events, for instance fall recognition. This thesis investigates an approach to apply those ideas to textile materials worn by users by embedding inertial measurement unit sensors in a non-intrusive manner. In our approach, a simulation framework is used to ensure the highest possible accuracy while keeping the amount of sensors needed as low as possible. For this, a simulated sensor grid across the whole jacket was evaluated. Later, a prototype which uses the deformation of the jacket to provide valuable information about the current state of the jacket will be introduced. The presented use case to help find the jacket is just one idea on how to use the information gained by the sensor network.enmachine learningContext-Awarenesssmart textileLead Topic: Smart CityResearch Line: Human computer interaction (HCI)006master thesis